MPhil Research Project:

 

This research describes a hybrid knowledge-based system, which gives advice on different aspects of a legal domain. The system employs two reasoning methods, rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated framework. It automates the estimation of the relative suitability of these reasoning methods for any given new problem description (i.e. know as case). The relative suitability is judged by matching the features of the selected best case and best rule against the new case. Standard methods of numerical taxonomy are used to determine which of the matches is best, and therefore whether a new case is better solved by calling on rules that express the usual legal knowledge in the area or by referring to a past case that has a interpretation of an ambiguous situation which rules fail to underpin.

 

Journal Publications:

 

[1] K. Pal, & J. A. Campbell, A hybrid legal decision-support system using both rule-based and case-based reasoning, Information and Communication Technology Law , 5(3), p.227-245, 1996.

 

 

[2] K. Pal, & J. A. Campbell, An Application of Rule-Based and Case-Based Reasoning within a Single Legal Knowledge-Based System, ACM SIGMIS Database, 28(4), p.48-63, 1997.

 

 

[3] K. Pal, An Approach to legal Reasoning Based on a Hybrid Decision-Support System, Expert Systems With Applications, 17(1), 1–12, 1999.

 

 

[4] K. Pal, & J. A. Campbell, ASHSD-II: A Computational model for litigation support, Expert Systems, 15(3), p.169-181, 1998.

 

[5] K. Pal, Evaluation of a Hybrid Knowledge-Based System Using Fuzzy Approach, International Journal of Computer, Electrical, Automation, Control, and Information Engineering, volume 9, issue 7, pages 1692-1698, 2015.

 

MBA Research Project:

 

This dissertation details work carried out as a project for the degree of Master in Business Administration (MBA) in Hull University and concern the analysis and design of a decision-support system for business acquisitions. This dissertation also describes the use of standard knowledge-based system design methodology, including knowledge elicitation, knowledge representation, and design techniques within a rapid prototyping environment.  The purpose of this project is to formulate and develop a computational prototype system to be used in the decision-making processes for business acquisitions. The main objectives of this project are as follows: (i) to understand the takeovers and acquisitions within the United Kingdom (UK) business environment; (ii) to identify the sources of regulations of takeovers and acquisitions cases; (iii) to set out and explore a way to design a computerised model of acquisitions for UK business; and (iv) to determine the suitability of the proposed model with real-world cases.

 

Journal Publication:

 

[1] K. Pal, & O. Palmer, A Decision-Support System for Business Acquisitions, Decision Support Systems, 27(4), p. 411-429, 2000.

 

Abstract: 

 

In this paper, a hybrid Decision-support System for Business Acquisition Process (DSBAP) is presented. This application uses a hybrid knowledge-based system to place a bidding on the target company, formulating a strategy, and modification of the initial strategy (if necessary) for the acquisition processes. The whole system relies on two reasoning methods, rule-based reasoning (RBR) and case-based reasoning (CBR) to assist in the decision-making process for business professionals. It also describes an argument structure to generate plausible explanations for a conclusion reached by RBR and a means of integrating with CBR. The RBR module dominates, but activities CBR explicitly at specific points in the reasoning process. The knowledge in rule form and previously decided case form is represented by using an object-oriented scheme. An overview of the functionality of the DSBAP system and a description of the represented knowledge are presented through the example of a set of business acquisition case.

 

Keywords: Hybrid decision-support system; Financial application of knowledge-based system; Rule-based reasoning; Case-based reasoning; Business acquisition

 

Conference Papers:

 

K. Pal, Agent-Based Simulation for Supply Chain Transport Corridors, International Journal of Computer, Electrical, Automation, Control, and Information Engineering, volume 9, issue 7, 2015.

 

K. Pal & B. Karakostas, A Critiquing Mechanism in Engineering Machine Design, Virtual and Networked Organizations, Emergent Technologies and Tools, Porto, Portugal, 263-272, 2012.

 

B. Karakostas & K. Pal, Orchestrating Inter-organizational Logistics Workflows on the Cloud, Virtual and Networked Organizations, Emergent Technologies and Tools, Porto, Portugal, 137-144, 2012.

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Selected Book Chapters:

 

[1] K.Pal,  Building High Quality Big Data-Based Applications in Supply Chains, A Kumar, S. Saurav (Edited); IGI Global Publication, December 2017, USA, ISBN 9781522530565

 

Abstract:  Global retail business has become diverse and latest Information Technology (IT) advancements have created new possibilities for the management of the deluge of data generated by world-wide business operations of its supply chain. In this business, external data from social media and supplier networks provide a huge influx to augment existing data. This is combined with data from sensors and intelligent machines, commonly known as Internet of Things (IoT) data. This data, originating from the global retail supply chain, is simply known as Big Data – because of its enormous volume, the velocity with which it arrives in the global retail business environment, its veracity to quality related issues, and values it generates for the global supply chain. Many retail products manufacturing companies are trying to find ways to enhance their quality of operational performance while reducing business support costs. They do this primarily by improving defect tracking and better forecasting. However, there are increasingly data quality problems resulting in erroneous testing costs in retail Supply Chain Management (SCM). The heavy investment made in Big Data-based software applications puts increasing pressure on management to justify the quality assurance in these software systems. This chapter discusses about data quality and the dimensions of data quality and governance of Big Data, and how those can be balance with the need of delivery usable Big Data-based software systems. Finally, the chapter highlights the importance of data governance; and it also include some of the Big Data managerial practice related issues and their justifications for achieving application software quality assurance.

 

 

Keywords: Supply Chain Management, Big Data Quality Assurance, Recommendation Systems, Prediction Systems, Decision Support System

 

 

[2] K.Pal, Supply Chain Coordination Based on Web Service, Supply Chain Management in the Big Data Era, H K. Chan, N Subramanian, M. D. Abdulrahman (Edited), IGI Global Publication, December 2016, USA, ISBN 9781522509578

 

 

Abstract: The importance of integrating and coordinating supply chain business partners have been appreciated in many industries. In the global manufacturing industry, supply chain business partners' information integration is technically a daunting task due to highly disconnected infrastructures and operations. Information, software applications, and services are loosely distributed among participant business partners with heterogeneous operating infrastructures. A secure and flexible information exchange architecture that can interconnect distributed information and share that information across global service provision applications is, therefore, immensely advantageous. This chapter describes the main features of an ontology-based web service framework for integrating distributed business processes in a global supply chain. A Scalable Web Service Discovery Framework (SWSDF) for material procurement systems of a manufacturing supply chain is described. Description Logic (DL) is used to represent and explain SWSDF. The framework uses a hybrid knowledge-based system, which consists of Case-Based Reasoning (CBR) and Rule-Based Reasoning (RBR). SWSDF includes: (1) a collection of web service descriptions in Ontology Web Language-Based Service (OWL-S), (2) service advertisement using complex-concepts, and (3) a service concept similarity assessment algorithm. Finally, a business scenario is used to demonstrate the functionalities of the described system.

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Keywords: Supply Chain Management, Semantic Web Service, Description Logic, Case-Based Reasoning, Rule-Based Reasoning

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[3] K.Pal, B. Karakostas, A Game-Based Approach for Simulation and Design of Supply Chains, Sustainable Logistics and Strategic Transportation Planning; T. Kramberger, V. Potocan, V. M Ipavec (Edited); IGI Global Publication, 2016, USA, ISBN 9781522500025

 

Abstract: This chapter reviews the potential benefits and challenges of knowledge-based computer game simulation as a means of understanding the dynamics of global procurement and manufacturing supply chains. In particular, the chapter focuses on software agents to assist decision making across the supply chain, for example in raw material procurement. The chapter describes a framework for supply chain scenarios in multi-agent based simulation games. The agents' behaviour is governed by the business rules, based on the concept of normative knowledge representation and its reasoning mechanism (known as rule-based reasoning, RBR), and that also come closer to the task that confronts the supply chain operation manager - the analysis of the current case in hand in terms of previously decided business problem solutions, known as case-based reasoning (CBR). The aim is to introduce more realistic behaviour of the supply chain actors and improve understanding in operational management of supply chains.

 

 

Keywords: Supply Chain Management, Operational Management, Computer Game Simulation, Global Procurement, Case-Based Reasoning, Rule-Based Reasoning

 

 

[4] K.Pal, B. Karakostas (2013), The Use of Cloud Computing in Shipping Logistics; D. Graham, I Manikas, D. Folinas (Edited); IGI Global Publication, 2013, USA, ISBN 9781466639164